Evaluating the Arm Ecosystem for High Performance Computing

In recent years, Arm-based processors have arrived on the HPC scene, offering an alternative the existing status quo, which was largely dominated by x86 processors. In this paper, we evaluate the Arm ecosystem, both the hardware offering and the software stack that is available to users, by benchmarking a production HPC platform that uses Marvell's ThunderX2 processors. We investigate the performance of complex scientific applications across multiple nodes, and we also assess the maturity of the software stack and the ease of use from a users' perspective. This papers finds that the performance across our benchmarking applications is generally as good as, or better, than that of well-established platforms, and we can conclude from our experience that there are no major hurdles that might hinder wider adoption of this ecosystem within the HPC community.Comment: 18 pages, accepted at PASC19, 1 figur

Solving inverse problems for medical applications

It is essential to have an accurate feedback system to improve the navigation of surgical tools. This thesis investigates how to solve inverse problems using the example of two medical prototypes. The first aims to detect the Sentinel Lymph Node (SLN) during the biopsy. This will allow the surgeon to remove the SLN with a small incision, reducing trauma to the patient. The second investigates how to extract depth and tissue characteristic information during bone ablation using the emitted acoustic wave. We solved inverse problems to find our desired solution. For this purpose, we investigated three approaches: In Chapter 3, we had a good simulation of the forward problem; namely, we used a fingerprinting algorithm. Therefore, we compared the measurement with the simulations of the forward problem, and the simulation that was most similar to the measurement was a good approximation. To do so, we used a dictionary of solutions, which has a high computational speed. However, depending on how fine the grid is, it takes a long time to simulate all the solutions of the forward problem. Therefore, a lot of memory is needed to access the dictionary. In Chapter 4, we examined the Adaptive Eigenspace method for solving the Helmholtz equation (Fourier transformed wave equation). Here we used a Conjugate quasi-Newton (CqN) algorithm. We solved the Helmholtz equation and reconstructed the source shape and the medium velocity by using the acoustic wave at the boundary of the area of interest. We accomplished this in a 2D model. We note, that the computation for the 3D model was very long and expensive. In addition, we simplified some conditions and could not confirm the results of our simulations in an ex-vivo experiment. In Chapter 5, we developed a different approach. We conducted multiple experiments and acquired many acoustic measurements during the ablation process. Then we trained a Neural Network (NN) to predict the ablation depth in an end-to-end model. The computational cost of predicting the depth is relatively low once the training is complete. An end-to-end network requires almost no pre-processing. However, there were some drawbacks, e.g., it is cumbersome to obtain the ground truth. This thesis has investigated several approaches to solving inverse problems in medical applications. From Chapter 3 we conclude that if the forward problem is well known, we can drastically improve the speed of the algorithm by using the fingerprinting algorithm. This is ideal for reconstructing a position or using it as a first guess for more complex reconstructions. The conclusion of Chapter 4 is that we can drastically reduce the number of unknown parameters using Adaptive Eigenspace method. In addition, we were able to reconstruct the medium velocity and the acoustic wave generator. However, the model is expensive for 3D simulations. Also, the number of transducers required for the setup was not applicable to our intended setup. In Chapter 5 we found a correlation between the depth of the laser cut and the acoustic wave using only a single air-coupled transducer. This encourages further investigation to characterize the tissue during the ablation process

Optimizing the Performance of Parallel and Concurrent Applications Based on Asynchronous Many-Task Runtimes

Nowadays, High-performance Computing (HPC) scientific applications often face per- formance challenges when running on heterogeneous supercomputers, so do scalability, portability, and efficiency issues. For years, supercomputer architectures have been rapidly changing and becoming more complex, and this challenge will become even more com- plicated as we enter the exascale era, where computers will exceed one quintillion cal- culations per second. Software adaption and optimization are needed to address these challenges. Asynchronous many-task (AMT) systems show promise against the exascale challenge as they combine advantages of multi-core architectures with light-weight threads, asynchronous executions, smart scheduling, and portability across diverse architectures. In this research, we optimize the performance of a highly scalable scientific application using HPX, an AMT runtime system, and address its performance bottlenecks on super- computers. We use DCA++ (Dynamical Cluster Approximation) as a research vehicle for studying the performance bottlenecks in parallel and concurrent applications. DCA++ is a high-performance research software application that provides a modern C++ imple- mentation to solve quantum many-body problems with a Quantum Monte Carlo (QMC) kernel. QMC solver applications are widely used and are mission-critical across the US Department of Energy’s (DOE’s) application landscape. Throughout the research, we implement several optimization techniques. Firstly, we add HPX threading backend support to DCA++ and achieve significant performance speedup. Secondly, we solve a memory-bound challenge in DCA++ and develop ring- based communication algorithms using GPU RDMA technology that allow much larger scientific simulation cases. Thirdly, we explore a methodology for using LLVM-based tools to tune the DCA++ that targets the new ARM A64Fx processor. We profile all imple- mentations in-depth and observe significant performance improvement throughout all the implementations

Software for Exascale Computing - SPPEXA 2016-2019

This open access book summarizes the research done and results obtained in the second funding phase of the Priority Program 1648 "Software for Exascale Computing" (SPPEXA) of the German Research Foundation (DFG) presented at the SPPEXA Symposium in Dresden during October 21-23, 2019. In that respect, it both represents a continuation of Vol. 113 in Springer’s series Lecture Notes in Computational Science and Engineering, the corresponding report of SPPEXA’s first funding phase, and provides an overview of SPPEXA’s contributions towards exascale computing in today's sumpercomputer technology. The individual chapters address one or more of the research directions (1) computational algorithms, (2) system software, (3) application software, (4) data management and exploration, (5) programming, and (6) software tools. The book has an interdisciplinary appeal: scholars from computational sub-fields in computer science, mathematics, physics, or engineering will find it of particular interest

Plant Viruses: From Ecology to Control

Plant viruses cause many of the most important diseases threatening crops worldwide. Over the last quarter of a century, an increasing number of plant viruses have emerged in various parts of the world, especially in the tropics and subtropics. As is generally observed for plant viruses, most of the emerging viruses are transmitted horizontally by biological vectors, mainly insects. Reverse genetics using infectious clones—available for many plant viruses—has been used for identification of viral determinants involved in virus–host and virus–vector interactions. Although many studies have identified a number of factors involved in disease development and transmission, the precise mechanisms are unknown for most of the virus–plant–vector combinations. In most cases, the diverse outcomes resulting from virus–virus interactions are poorly understood. Although significant advances have been made towards understand the mechanisms involved in plant resistance to viruses, we are far from being able to apply this knowledge to protect cultivated plants from the all viral threats.The aim of this Special Issue was to provide a platform for researchers interested in plant virology to share their recent results. To achieve this, we invited the plant virology community to submit research articles, short communications and reviews related to the various aspects of plant virology: ecology, virus–plant host interactions, virus–vector interactions, virus–virus interactions, and control strategies. This issue contains some of the best current research in plant virology

Tackling the barriers to achieving Information Assurance

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.This original, reflective practitioner study researched whether professionalising IA could be successfully achieved, in line with the UK Cyber Security Strategy expectations. The context was an observed changing dominant narrative from IA to cybersecurity. The research provides a dialectical relationship with the past to improve IA understanding. The Academic contribution: Using archival and survey data, the research traced the origins of the term IA and its practitioner usage, in the context of the increasing use of the neologism of cybersecurity, contributing to knowledge through historical research. Discourse analysis of predominantly UK government reports, policy direction, legislative and regulatory changes, reviewing texts to explore the functions served by specific constructions, mainly Information Security (Infosec) vs IA. The Researcher studied how accounts were linguistically constructed in terms of the descriptive, referential and rhetorical language used, and the function that serves. The results were captured in a chronological review of IA ontology. The Practitioner contribution: Through an initial Participatory Action Research (PAR) public sector case study, the researcher sought to make sense of how the IA profession operates and how it was maturing. Data collection from self-professed IA practitioners provided empirical evidence. The researcher undertook evolutionary work analysing survey responses and developed theories from the analysis to answer the research questions. The researcher observed a need to implement a unified approach to Information Governance (IG) on a large organisation-wide scale. Using a constructivist grounded theory the researcher developed a new theoretical framework - i3GRC™ (Integrated and Informed Information Governance, Risk, and Compliance) - based on what people actually say and do within the IA profession. i3GRC™ supports the required Information Protection (IP) through maturation from IA to holistic IG. Again, using PAR, the theoretical framework was tested through a private sector case study, the resultant experience strengthening the bridge between academia and practitioners